doke93 / FPI_Report_Data_Analysis_Project

Exploratory data analysis project for 'Data Analysis with Python: Zero to Pandas' course on jovian platform

Objectives 🎯

The goal of this project is to understand the Foreign direct investment in India for the last 22 years from 2000-01 to 2021-22.

What is FPI?

• Foreign Investment inflow is an important reason for India’s economic growth. So to simplify compliance requirements and have uniform guidelines for various categories of foreign investors like Foreign Institutional Investors (FIIs), Sub Accounts and Qualified Foreign Investors (QFIs) merged into a new investor class termed as Foreign Portfolio Investors (FPIs).
• SEBI has authorized NSDL to monitor of these Group investment and various data related to FPI activities to be displayed on NSDL web portal.
• NSDL provides this data at an interval of 15 days.

Problem Statement ❓

Investment is a game of understanding historic data of investment objects under different events but it is still a game of chances to minimize the risk we apply analytics to find the equilibrium investment.

Dataset 📀

NSDL FPI REPORT

Technology �

Business Intelligence

Domain 🏥

Finance

Project Difficulty level 🥇

Advanced

Programming Language 🐍

Python

Tools 🛠

• Jupyter Notebook
• MS Excel

Conclusion 💡

• In this project we have compared FPIs data and Nifty indices data.
• It's worth noting that there's a delay in receiving the FPI Report; it's the 2nd of March,2022 as I write this notebook, and the report for February 28th 2022 is still unavailable.
• It was interesting to examine the pre and post lockdown scenarios,since the pharma sector showed a fund inflow as per FPIs data ,while the nifty pharma index displayed consolidation and following the first phase of lock-down, the pharma index began to rise.
• We also analysed financial data,which demonstrated a high correlation between Nifty Bank and Financial sector.
• As a result, we can conclude that FPI data can assist us in detecting early indications and can be used to get a better understanding of the Indian market before investing

Ideas for future work

• I have manually imported the FPI data from nsdl using google sheets and downloaded it as xlsx format, instead we can pharse the table using web scraping python library i.e Beautiful Soup or Selenium and maintain a SQL database.
• Further we can use FPIs data as one of the feature in machine learning model to backtest a trading strategy.
• We can also create an interactive dashboard using plotly and deploy it using streamlit or Django.

LinkedIn Post 📲

Post link

🎉 Help Me Improve

Hello Mr. Reader, if you find any bug or anything else that could add more value in this project then please consider raising it to me I will address them asap